SAA 考试每日练习 - 2024/11/12

来源：AWS解决方案架构师认证-助理级(SAA-C03)仿真练习题
3 题，免费题库，题目质量不高，仅供自己复习使用。
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🌟 单词：

parallel_{adj. 平行的，并列的 | v. 与……同时发生；与……相似；与…媲美；比得上 | n. 平行线，极其相似的人（或情况、事件等）}
loosely_{adv. 宽松地；松散地；不精确地}
couple_{v. 结合；交配 | n. 夫妻；情侣；一对，一双；不确定的小数目，两个，两三个，几个}
durable_{adj. 耐用的, 耐久的, 长期的, 长久的 | n. 耐久品}
scaling_{n. 测量, 【电】定标, 电子法计算电脉冲, 推列 | v. “scale” 的现在分词}
scenario_{n. 方案；设想; 可能发生的事，可能出现的情况，设想的场景；（电影、戏剧等的）剧情梗概}
predictive_{adj. 预测的, 预言的, 前瞻的}
maintenance_{n. 维护，保养；维持；（依法应负担的）生活费，抚养费}
machinery_{n. 机构, （统称）机器, （尤指）大型机器, 机器的运转部分}
equipment_{n. 设备, 装备, 器材, 配备}

一、Cross Region EC2 AMI Copy

A company’s application is running on Amazon EC2 instances in a single Region. In the event of a disaster, a solutions architect needs to ensure that the resources can also be deployed to a second Region.
Which combination of actions should the solutions architect take to accomplish this? (Choose two.)

Detach a volume on an EC2 instance and copy it to Amazon S3.
✅ Launch a new EC2 instance from an Amazon Machine Image (AMI) in a new Region.
Launch a new EC2 instance in a new Region and copy a volume from Amazon S3 to the new instance.
✅ Copy an Amazon Machine Image (AMI) of an EC2 instance and specify a different Region for the destination.
Copy an Amazon Elastic Block Store (Amazon EBS) volume from Amazon S3 and launch an EC2 instance in the destination Region using that EBS volume.

✨ 关键词：EC2、多区域

2️⃣ 4️⃣ ✅

💡 解析：We know that you want to build applications that span AWS Regions and we’re working to provide you with the services and features needed to do so. We started out by launching the EBS Snapshot Copy feature late last year. This feature gave you the ability to copy a snapshot from Region to Region with just a couple of clicks. In addition, last month we made a significant reduction (26% to 83%) in the cost of transferring data between AWS Regions, making it less expensive to operate in more than one AWS region.
Today we are introducing a new feature: Amazon Machine Image (AMI) Copy. AMI Copy enables you to easily copy your Amazon Machine Images between AWS Regions. AMI Copy helps enable several key scenarios including: Simple and Consistent Multi-Region Deployment “” You can copy an AMI from one region to another, enabling you to easily launch consistent instances based on the same AMI into different regions.
Scalability “” You can more easily design and build world-scale applications that meet the needs of your users, regardless of their location.
Performance “” You can increase performance by distributing your application and locating critical components of your application in closer proximity to your users.
You can also take advantage of region-specific features such as instance types or other AWS services.
Even Higher Availability “” You can design and deploy applications across AWS regions, to increase availability.
Once the new AMI is in an Available state the copy is complete. Reference: https://aws.amazon.com/blogs/aws/ec2-ami-copy-between-regions/

二、Amazon Simple Queue Service & Scaling Based on Amazon SQS

A solutions architect is designing the cloud architecture for a new application being deployed on AWS. The process should run in parallel_并行的 while adding and removing application nodes as needed based on the number of jobs to be processed. The processor application is stateless. The solutions architect must ensure that the application is loosely coupled and the job items are durably stored.
Which design should the solutions architect use?

Create an Amazon SNS topic to send the jobs that need to be processed. Create an Amazon Machine Image (AMI) that consists of the processor application. Create a launch configuration that uses the AMI. Create an Auto Scaling group using the launch configuration. Set the scaling policy for the Auto Scaling group to add and remove nodes based on CPU usage.
Create an Amazon SQS queue to hold the jobs that need to be processed. Create an Amazon Machine Image (AMI) that consists of the processor application. Create a launch configuration that uses the AMI. Create an Auto Scaling group using the launch configuration. Set the scaling policy for the Auto Scaling group to add and remove nodes based on network usage.
✅ Create an Amazon SQS queue to hold the jobs that need to be processed. Create an Amazon Machine Image (AMI) that consists of the processor application. Create a launch template that uses the AMI. Create an Auto Scaling group using the launch template. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue.
Create an Amazon SNS topic to send the jobs that need to be processed. Create an Amazon Machine Image (AMI) that consists of the processor application. Create a launch template that uses the AMI. Create an Auto Scaling group using the launch template. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of messages published to the SNS topic.

✨ 关键词：SQS

3️⃣ ✅

💡 解析：Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. SQS eliminates the complexity and overhead associated with managing and operating message oriented middleware, and empowers developers to focus on differentiating work. Using SQS, you can send, store, and receive messages between software components at any volume, without losing messages or requiring other services to be available. Get started with SQS in minutes using the AWS console, Command Line Interface or SDK of your choice, and three simple commands.
SQS offers two types of message queues. Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery. SQS FIFO queues are designed to guarantee that messages are processed exactly once, in the exact order that they are sent.
There are some scenarios where you might think about scaling in response to activity in an Amazon SQS queue. For example, suppose that you have a web app that lets users upload images and use them online. In this scenario, each image requires resizing and encoding before it can be published. The app runs on EC2 instances in an Auto Scaling group, and it’s configured to handle your typical upload rates. Unhealthy instances are terminated and replaced to maintain current instance levels at all times. The app places the raw bitmap data of the images in an SQS queue for processing. It processes the images and then publishes the processed images where they can be viewed by users. The architecture for this scenario works well if the number of image uploads doesn’t vary over time. But if the number of uploads changes over time, you might consider using dynamic scaling to scale the capacity of your Auto Scaling group.
Reference: https://aws.amazon.com/sqs/#:~:text=Amazon%20SQS%20leverages%20the%20AWS,queues%20provide%20nearly%20unlimited%20throughput https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-using-sqs-queue.html

三、Amazon Kinesis Data Streams

A manufacturing company wants to implement predictive_前瞻的 maintenance_维护 on its machinery equipment. The company will install thousands of IoT sensors that will send data to AWS in real time. A solutions architect is tasked with implementing a solution that will receive events in an ordered manner for each machinery asset and ensure that data is saved for further processing at a later time.
Which solution would be MOST efficient?

✅ Use Amazon Kinesis Data Streams for real-time events with a partition for each equipment asset. Use Amazon Kinesis Data Firehose to save data to Amazon S3.
Use Amazon Kinesis Data Streams for real-time events with a shard for each equipment asset. Use Amazon Kinesis Data Firehose to save data to Amazon EBS.
Use an Amazon SQS FIFO queue for real-time events with one queue for each equipment asset. Trigger an AWS Lambda function for the SQS queue to save data to Amazon EFS.
Use an Amazon SQS standard queue for real-time events with one queue for each equipment asset. Trigger an AWS Lambda function from the SQS queue to save data to Amazon S3.

✨ 关键词：Amazon Kinesis Data、S3

1️⃣ ✅

💡 解析：无。